3 citations · 7 across the 6 of their papers we have counts for
6 papers
Reason to Play: Behavioral and Brain Alignment Between Frontier LRMs and Human Game Learners
Botos Csaba, Sreejan Kumar, Austin Tudor David Andrews +6
Humans rapidly learn abstract knowledge when encountering novel environments and flexibly deploy this knowledge to guide efficient and intelligent action. Can modern AI systems lea…
Near to Mid-term Risks and Opportunities of Open-Source Generative AI
Francisco Eiras, Aleksandar Petrov, Bertie Vidgen +21
In the next few years, applications of Generative AI are expected to revolutionize a number of different areas, ranging from science & medicine to education. The potential for thes…
Label Delay in Online Continual Learning
Botos Csaba, Wenxuan Zhang, Matthias Müller +4
Online continual learning, the process of training models on streaming data, has gained increasing attention in recent years. However, a critical aspect often overlooked is the lab…
Diversified Dynamic Routing for Vision Tasks
Botos Csaba, Adel Bibi, Yanwei Li +2
Deep learning models for vision tasks are trained on large datasets under the assumption that there exists a universal representation that can be used to make predictions for all s…
Multilevel Knowledge Transfer for Cross-Domain Object Detection
Botos Csaba, Xiaojuan Qi, Arslan Chaudhry +2
Domain shift is a well known problem where a model trained on a particular domain (source) does not perform well when exposed to samples from a different domain (target). Unsupervi…
Domain Partitioning Network
Botos Csaba, Adnane Boukhayma, Viveka Kulharia +2
Standard adversarial training involves two agents, namely a generator and a discriminator, playing a mini-max game. However, even if the players converge to an equilibrium, the gen…